A recent assessment of the capabilities of current proteomics technologies states that "the top proteomics labs can identify and quantify more than 6,000 distinct proteins from individual cells and tissues at a time" and this number is probably close to the maximum number of proteins known in plasma. Strikingly however, it has been estimated that human plasma contains 550,000 "protein forms" (excluding immunoglobulins), leaving over 500,000 distinct species to discover. Although there are discussions underway about a Human Proteome Project to "survey the landscape of human proteins", such an effort, which is thought to potentially cost hundreds of millions to billions of dollars and take decades to complete, does not seem to be immediately viable in the current funding environment. Therefore at present there is apparently no general, scalable, and cost- and time- effective proposal for discovering the approximately 98% of the remaining plasma proteome. One of the major hurdles for detecting novel plasma proteins has been the approximately 10 orders of magnitude relative abundance difference between serum albumin (35-50 x 109 pg/ml) and low abundance proteins such as Interleukin-6 (0-5 pg/ml). This application evaluates both peptide and antibody phage display libraries, using either native or reduced and alkylated proteins for sample preparation, to determine which library type and protein epitope composition will detect the greatest number of novel proteins. It then seeks to test an innovative approach to fractionate plasma, on the basis of relative protein abundance to allow detection of the lower abundance species. These studies will demonstrate proof-of-principle data to support the large- scale generation of novel protein/affinity capture sets for biomarker discovery and validation by the Bioscience Research &Development community. Specific Aim 1: To determine whether a pool of random peptide phage libraries or an scFv antibody phage library, for either the native proteins or the reduced and alkylated proteins, will yield the most comprehensive plasma proteome coverage. Specific Aim 2: To test the performance of a plasma protein fractionator procedure in revealing novel protein species not previously detected with current proteomics technologies. PUBLIC HEALTH RELEVANCE: At present only about 2% of the human plasma proteome is known, and there is no general, scalable, and cost- and time- effective method available for discovering the approximately 98% of the remaining plasma proteome. This project will investigate a new cost- and time- effective approach to the large-scale generation of novel protein/affinity capture sets for biomarker discovery and validation by the Bioscience Research &Development community.